Name
Abstract | ||
|---|---|---|
Modeling and predicting citation dynamics of individual articles is important due to its critical role in a wide range of decisions in science. While the current modeling framework successfully captures citation dynamics of typical articles, there exists a nonnegligible, and perhaps most interesting, fraction of atypical articles whose citation trajectories do not follow the normal rise-and-fall pattern. Here we systematically study and classify citation patterns of atypical articles, finding that they can be characterized by awakened articles, second-acts, and a combination of both. We propose a second-act model that can accurately describe the citation dynamics of second-act articles. The model not only provides a mechanistic framework to understand citation patterns of atypical articles, separating factors that drive impact, but it also offers new capabilities to identify the time of exogenous events that influence citations. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1002/asi.24041 | JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY |
Field | DocType | Volume |
Existential quantification,Information retrieval,Computer science,Citation | Journal | 69.0 |
Issue | ISSN | Citations |
9.0 | 2330-1635 | 0 |
PageRank | References | Authors |
0.34 | 14 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhongyang He | 1 | 0 | 0.34 |
| Zhen Lei | 2 | 2 | 1.74 |
| Dashun Wang | 3 | 627 | 27.09 |